Networks, such as the Internet, have become an increasingly important part of our everyday lives. Millions of people now access the Internet on a daily basis to shop for goods and services, obtain information of interest (e.g., movie listings), and to communicate with friends, family, and co-workers (e.g., via e-mail).
Currently, when a person wishes to purchase a product or simply find information on the Internet, the person enters into his/her web browser a Uniform Resource Locator (URL) pertaining to a web site of interest in order to access that particular web site. The person then determines whether the information of interest is available at that particular web site.
For example, suppose an individual wishes to purchase a printer via the Internet. The individual accesses the Internet and types in a vendor's URL. The individual may then access that vendor's home page to determine whether the vendor has the product that this individual wishes to purchase.
If the individual is not aware which vendors sell printers, the individual may access a web site that includes a conventional search engine. The individual enters the generic term “printer” into the search engine to attempt to locate a vendor that sells printers. Using a search engine in this manner to locate individual web sites that offer the desired product or service often results in a list of hundreds or even thousands of “hits,” where each hit may correspond to a web page that relates to the search term.
In addition, the search engine web site may provide companies' advertisements relating to the product or service to which the individual is interested. For the example above, the search engine web site may provide advertisements for printers. The search engine web site may charge companies a predetermined fee each time the companies' advertisements are displayed to a user of the search engine web site. A more recent trend is to charge companies a fee each time their advertisement is selected by a user (i.e., each time a user clicks on the displayed advertisement).
This latter fee approach, however, is vulnerable to click spam attacks where malicious individuals (or competitors) inflate a company's click count by, for example, continually physically clicking on the company's advertisement or writing programs that automatically access (although these programs do not necessarily “click” the advertisement, “clicking” hereinafter generally refers to physical clicking of an advertisement, as well as programs that automatically access an advertisement) the company's advertisement. That is, a company may be charged for clicks that do not correspond to real (or normal) users. This often results in the company having to unnecessarily pay more.
Current attempts to detect click spamming rely on identifying the click spammers. As click spamming techniques become more sophisticated, it becomes more difficult to identify these malicious individuals.
Therefore, there exists a need for systems and methods for improving the detection of click spam attacks.